REQUIREMENTS

• 7+ years of backend engineering, including 3+ years at Staff/Principal scope leading complex, distributed platforms.
• Deep expertise with Node.js in production; comfortable pushing the runtime’s limits when appropriate.
• Polyglot architecture experience (e.g., Go, Rust, Elixir/Erlang, or modern Java) and sound judgment on when to use each.
• Strong PostgreSQL fundamentals: schema design, query tuning, and scaling strategies for high-write, high-read workloads.
• Hands-on experience shipping ML/LLM features to production, with clear understanding of their strengths and limits.
• Proven track record building systems for millions of concurrent users and real-time requirements.
• Cloud-native development at scale (GCP experience a plus): microservices, containers, event buses, and observability.
• Mindset: mission-first, data-driven, collaborative, and committed to responsible AI that augments (not replaces) teachers.
  Work location: Primarily on-site in one of two U.S. hubs (Central and West Coast). Relocation support available.
  Work authorization: Unable to sponsor visas at this time.

ABOUT THE ROLE

They’re hiring a Staff-level Backend Engineer to architect and scale the core services that power individualized learning experiences for millions of students. You’ll lead the design of data-intensive, AI-driven systems, set technical direction across services, and collaborate closely with educators and researchers to translate pedagogy into production software.

RESPONSIBILITIES

• Design and evolve adaptive learning backends that process massive streams of learner interactions and respond in real time.
• Build orchestration layers for LLM/ML workloads that deliver safe, reliable personalization at scale.
• Develop intelligent content and feedback services that time the right hint, explanation, or challenge to each learner.
• Establish privacy, safety, and governance controls that protect student data while enabling responsible AI.
• Create real-time assessment services and knowledge graph components that capture conceptual understanding, not just right/wrong.
• Architect multi-modal pipelines supporting visual, auditory, and kinesthetic learning experiences.
• Drive reliability and performance across distributed systems (low-latency APIs, event-driven pipelines, and high-availability services).
• Optimize for cost and efficiency; design for constrained networks and offline-first scenarios to broaden access.
• Partner with teachers, students, and learning scientists to ensure solutions work in real classrooms.
• Raise the engineering bar through mentorship, code reviews, and pragmatic technical leadership; contribute to open source where it helps the ecosystem.